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import os
import requests
import gradio as gr
import openai
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# Initialize OpenAI client
openai.api_key = os.getenv("OPENAI_API_KEY1")
# Define function to get current weather
def get_current_weather(location, unit='celsius'):
weather_api_key = os.getenv("WEATHER_API_KEY")
base_url = f"http://api.openweathermap.org/data/2.5/weather?q={location}&appid={weather_api_key}&units=metric"
try:
response = requests.get(base_url, timeout=10) # Increased timeout for the request
response.raise_for_status() # Check if the request was successful
data = response.json()
weather_description = data['weather'][0]['description']
return {
"location": location,
"temperature": data['main']['temp'],
"weather": weather_description
}
except requests.exceptions.Timeout:
return {"error": "Request timed out. Please try again later."}
except requests.exceptions.RequestException as e:
print(f"Request failed: {e}")
return {"error": str(e)}
# Function definition and initial message handling
def weather_chat(user_message):
messages = []
messages.append({"role": "user", "content": user_message})
messages.append({"role": "assistant", "content": "You are a weather bot. Answer only in Celsius. If two cities are asked, provide weather for both."})
# Sending initial message to OpenAI
try:
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
temperature=0,
max_tokens=256,
top_p=1,
frequency_penalty=0,
presence_penalty=0,
messages=messages,
functions=[
{
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city, e.g. San Francisco"},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
},
"required": ["location"]
}
}
]
)
except Exception as e:
print(f"OpenAI API call failed: {e}")
return "Failed to communicate with the OpenAI API. Please try again later."
# Handling function calls and fetching weather data
try:
function_call = response['choices'][0]['message']['function_call']
arguments = eval(function_call['arguments'])
weather_data = get_current_weather(arguments['location'])
if 'error' in weather_data:
return weather_data['error']
messages.append({"role": "assistant", "content": None, "function_call": {"name": "get_current_weather", "arguments": str(arguments)}})
messages.append({"role": "function", "name": "get_current_weather", "content": str(weather_data)})
# Continue conversation with weather data
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=messages
)
return response['choices'][0]['message']['content']
except Exception as e:
print(f"Error during processing: {e}")
return "I'm here to provide weather updates. Please ask me questions related to weather."
# Define Gradio interface
iface = gr.Interface(
fn=weather_chat,
inputs=gr.Textbox(label="Weather Queries"),
outputs=gr.Textbox(label="Weather Updates"),
title="DDS Weather Bot",
description="Ask me anything about weather!"
)
# Launch the Gradio interface
iface.launch(share=True)
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